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Record W2280887705 · doi:10.5038/1911-9933.9.3.1317

Dangerous Speech and Dangerous Ideology: An Integrated Model for Monitoring and Prevention

2016· article· en· W2280887705 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueGenocide Studies and Prevention · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicMiddle East and Rwanda Conflicts
Canadian institutionsnot available
Fundersnot available
KeywordsIdeologyGenocideTribunalCriminologyPolitical scienceLawWar crimeSociologyInternational lawPolitics

Abstract

fetched live from OpenAlex

There is considerable agreement amongst scholars and international actors that ideologies and speech play a critical role in the path of escalation towards mass atrocity crimes. Speech features prominently in the jurisprudence of the U.N. war crimes tribunal for Rwanda, for example, and in historical accounts of the months and years preceding many other genocides. Nonetheless, this is one of the most underdeveloped components of genocide and atrocity prevention, in both theory and practice. This paper draws together the authors’ independent past work on dangerous speech and the ideological dynamics of mass atrocities by offering a new integrated model to help identify the sorts of speech and ideology that raise the risk of atrocities and genocides. We suggest that this model should inform monitoring activities concerned with the risk of genocides and mass atrocities, and prevention efforts at the strategic and targeted levels.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.979
Threshold uncertainty score0.523

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.091
GPT teacher head0.371
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it